Triple
T34077170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perrottet government |
E873936
|
entity |
| Predicate | cabinetNumberInNSW |
P17175
|
FINISHED |
| Object | 99th ministry of New South Wales |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 99th ministry of New South Wales | Statement: [Perrottet government, cabinetNumberInNSW, 99th ministry of New South Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cabinetNumberInNSW Context triple: [Perrottet government, cabinetNumberInNSW, 99th ministry of New South Wales]
-
A.
cabinetNumberInNorway
Indicates the specific ordinal number of a Norwegian government cabinet within the historical sequence of cabinets in Norway.
-
B.
cabinetNumberInHistory
chosen
Indicates the specific cabinet number assigned to an entity within a historical record or context.
-
C.
cabinetNumberInNetherlands
Indicates the specific numbered term or sequence position of a government cabinet within the Netherlands.
-
D.
hasCabinetNumberingSystem
Indicates that there is a specific scheme or method used to assign and organize identification numbers to cabinets.
-
E.
numberOfCabinet
Indicates the quantity of cabinets associated with a given entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349a566808190a1c63b898f33cddf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:52 a.m.